Senior Data Platform Engineer
At IHS Markit, we are building a software solution that connects data in revolutionary ways, illuminating answers that were previously impossible to find and empowering our clients to envision the future, so they can determine the best course of action in the present. We are disrupting the current digital transformation landscape with state-of-the-art AI developed by a passionate team to explore and push the boundaries of digital transformation technologies.
Our development and AI teams produce and consume a wide variety and volume of high impact data which support innovative and intelligent solutions. Experts in the subdomains of software engineering and artificial intelligence, our teams have a need for expertly crafted, scalable, and accessible data platforms from which to assemble and deliver “self-service” data pipelines. All of our new products are developed using a microservice architecture, are containerized, and are then deployed on container management systems such as Kubernetes. Our teams subscribe to a model where time-to-market functions as a vital measure of our performance, productivity, and success. We are committed to staying ahead of the curve and are always looking at new technologies and methodologies to achieve that aim.
IHS Markit is seeking an adept, action-oriented Senior Data Platform Engineer based in Denver, CO who will report to the Principal Data Platform Engineer for our currently unreleased digital transformation solution. The candidate has experience deploying big data technologies and infrastructure (e.g. Kafka, Spark, DynamoDB, Neo4j), building frameworks atop to facilitate autonomous use for internal customers, and abstracting production solutions so they feel like “magic” for stakeholders such that things “just fall into place.” As Senior Data Platform Engineer, you are hands-on, data-driven, and highly collaborative. You should enjoy being "full stack" in the sense that you own a product from beginning to end by designing, constructing, integrating, testing, documenting, and supporting your creations. You have a passion for engineering best-practices and the ability to lucidly communicate with fellow engineers as well as non-technical colleagues. You don’t just subscribe to a single language or paradigm but are dedicated to learning new tools, technologies, and design patterns.
- Develop and deploy production-grade services, SDK’s, and data infrastructure emphasizing performance, scalability, and self-service.
- Assume a leadership role in developing solutions with experience in continuous delivery, immutable deployments, containerization, and micro-service architectural patterns.
- Are “biased to action” and not easily blocked by problems and difficulties, instead taking ownership
- Believe in monitoring, QA, and security as a first-class citizen in any data product.
- Excited to build data platforms and tools that abstract implementation details for developers, analysts, and data scientists, enabling data transit and storage “as a service.”
- Dedicated to automation, documentation, and collaboration at all stages of the engineering workflow.
- Passionate about mentoring colleagues and educating the organization on data engineering best practices.
- Maintain a firm understanding of the business long term goals and strategy to inform system implementation - able to see the forest through the trees.
Education / Experience
- Degree in Computer Science, related field or equivalent experience.
- Four (4) or more years of increasing responsibility in technical data roles, with 1 or more years of experience in guiding a data engineer team.
- Experience in productionizing various big data technologies both open source and cloud native, AWS preferred (Kafka/Kinesis, Presto/Athena, Spark/EMR, Airflow, Hive, Drill).
- Expertise in data model design with sensitivity to usage patterns and goals – schema, scalability, immutability, idempotency, etc.
- Expertise in of at least two of the following languages – Scala, Java, Python, Go.
- Experience in the full suite of NoSQL models and frameworks – especially large graphs.
- Track record of choosing the right transit, storage, and analytical technology to simplify and optimize user experience.
- Real-world experience developing highly scalable solutions using micro-service architecture designed to democratize data to everyone in the organization.
- Able to function autonomously and successfully in ambiguous situations.